Emily Keller-O'Donnell, Journalist

As Washington Students Head Back to Class, Seismic Building Data is Hard to Find

As the start of the upcoming school year approaches, many students in Washington State will be attending schools that may be unsafe in a major earthquake. However, following years of modernization efforts and millions of dollars spent on renovations and reconstruction to enable school buildings to better withstand a major tremor, information about the seismic readiness of school buildings remains difficult to obtain. While information is available on a case-by-case basis depending on the district, there is no publicly available state database to search for individual schools, and the available resources are sometimes out of date.

Read the full article here.

Seismic Retrofitting of Washington State Schools Would Cost Billions

The passage of a Washington State bill providing planning and construction funds to protect K-12 public schools against earthquake destruction came as welcome news last year. The bill’s passage followed the completion of the School Seismic Safety Project (SSSP), which provided geological and engineering assessments of 561 school buildings, and rated 93 percent of those buildings with just 1 out of 5 stars for structural safety using national seismic evaluation criteria.

The SSSP assessed approximately 14 percent of the state's more than 4,000 school buildings for grades K-12 from across the state. The school selection criteria included a higher proportion of buildings constructed prior to the adoption of modern seismic standards in 1998, and those that are located in tsunami inundation zones, as identified by the Washington Geological Survey. Overall, 63 percent of the assessed buildings were found to have a "high" or "very high" seismic risk, compared with “moderate” or “lower” risks.

Read the full article here.

Virginia, the Data Center Capital of the World, Has a Higher Percentage of Households Without Internet Than Most U.S. States

Survey results from the U.S. Census showed a higher percentage of households in Virginia lacked home Internet access in November 2021 than at any other point in which data was collected over the last ten years. About 34 percent of households in Virginia said they did not have home Internet access, second only to Idaho (39 percent) and Nebraska (37 percent). On average, 23 percent of U.S. households said they did not have home Internet in the 2021 survey.

This comes as the number of data centers providing global Internet access have grown significantly across the region, making Northern Virginia the world leader in the prevalence of data center operations and construction, as measured by the number of data centers and their total power capacity.

Read the full article here.

DSSG Teams Present Their Final Project Results

Student fellows at the University of Washington Data Science for Social Good (DSSG) program presented the results of their 10-week summer projects on August 17th. The fellows conducted their work on four interdisciplinary teams, working with project leads and data scientists. 

Read the full article at eScience News here.

Interdisciplinary Team Designs Database to Advance ‘Self-Sufficiency Standard’ Research

Determining the income level that working families need to meet their basic needs requires a dynamic approach. An interdisciplinary team at the University of Washington (UW) Data Science for Social Good (DSSG) program is laying the groundwork for the integration of multi-sourced data from across the U.S. to provide researchers and policy makers with an expanded breadth of opportunities for analyzing complex information in new ways.

The project is centered on designing and testing a database for the Self-Sufficiency Standard, a project of the Center for Women’s Welfare at the UW School of Social Work that determines the income level required for working families to meet their minimum basic needs, based on family composition, children’s ages, and geographic differences in the cost of living. The Standard provides an alternative to the Official Poverty Measure that is currently used to calculate eligibility for benefits such as housing subsidies and food assistance across the U.S.

Read the full article at eScience News here.

Applying ‘Geospatial First’ Approach to Estimating Heating Loads in Alaska

Decarbonization efforts to mitigate the impacts of climate change face a unique challenge in Alaska. While about 70 percent of energy use in the state goes to heating, there is a lack of reliable broad-scale data on the portion of energy that is used for heating in buildings. An interdisciplinary team at the University of Washington Data Science for Social Good (DSSG) program is working to create an improved method for estimating thermal energy use in buildings in the Alaska Railbelt and Arctic regions, to support these efforts.

Read the full article at eScience News here.

OpenSidewalks Collaboration Wins METRO Innovative Solutions Award

A METRO Innovative Solutions Award was recently awarded to King County Metro (KCM) and MV Transportation for the development of CommonPaths, a new application that collects and integrates granular data about sidewalk and pathway conditions that influence pedestrian mobility, including for people with disabilities. The application can provide a basis for generating automated accessibility condition analysis, providing navigation instructions, and supporting transportation planning and research.

Read the full article at the Cascadia Urban Analytics Cooperative website here.

Data Science for Social Good Fellows Present Their Project Results

This year, two interdisciplinary teams at the eScience Institute’s Data Science for Social Good (DSSG) program tackled timely issues, conducting projects to identify disinformation articles about the coronavirus and detect minority vote dilution resulting from geographic boundary setting in state, city, county and school board districts.

On August 19th, the DSSG student fellows presented the results of their projects, conducted with project leads and data scientists, to more than 130 people via zoom.  The ten-week summer program joins student fellows from universities around the country with data and domain researchers, and real-world stakeholders, to work on collaborative projects for societal benefit. This year the program took place remotely for the first time due to the coronavirus pandemic.

Read the full article at eScience News here.

Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing

Meg Young, Luke Rodriguez, Emily Keller, Feiyang Sun, Boyang Sa, Jan Whittington, and Bill Howe. 2019. Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing. In Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT* '19). Association for Computing Machinery, New York, NY, USA, 191–200. https://doi.org/10.1145/3287560.3287577

Guidance for Responsible Big Data Research

“Ten simple rules for responsible big data research,” published in PLoS Computational Biology, provides practical guidance for big data researchers on the complexities of privacy protections, preventing re-identification of research subjects, and recognizing the difference between publicly available data and user consent for third-party research. This paper represents the work of the Council for Big Data, Ethics, and Society, funded by the National Science Foundation grant # IIS-1413864.

Authors: Matthew Zook, Solon Barocas, danah boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, and Frank Pasquale, March 30, 2017.

Read the paper here.